Hala D
Department of Marine Biology, Texas A&M University at Galveston, 200 SeaWolf Parkway, Galveston, TX, 77553, USA.
J Theor Biol. 2017 Mar 21;417:51-60. doi: 10.1016/j.jtbi.2017.01.027. Epub 2017 Jan 19.
The interconnected topology of transcriptional regulatory networks (TRNs) readily lends to mathematical (or in silico) representation and analysis as a stoichiometric matrix. Such a matrix can be 'solved' using the mathematical method of extreme pathway (ExPa) analysis, which identifies uniquely activated genes subject to transcription factor (TF) availability. In this manuscript, in silico multi-tissue TRN models of brain, liver and gonad were used to study reproductive endocrine developmental programming in zebrafish (Danio rerio) from 0.25h post fertilization (hpf; zygote) to 90 days post fertilization (dpf; adult life stage). First, properties of TRN models were studied by sequentially activating all genes in multi-tissue models. This analysis showed the brain to exhibit lowest proportion of co-regulated genes (19%) relative to liver (23%) and gonad (32%). This was surprising given that the brain comprised 75% and 25% more TFs than liver and gonad respectively. Such 'hierarchy' of co-regulatory capability (brain<liver<gonad) indicated presence of highly gene-specific TRNs in the brain, alluding to its role as 'master controller' of endocrine function. Second, TRN models were constrained with varying TF availabilities during zebrafish development. Normalized numbers of genes active during development showed concomitant activations between brain and gonad from 10 to 12 hpf (embryonic life stage) up to 30-90 dpf (adult life stage). This indicated a putative 'syncing' between the brain and gonad, and initiation of an early reproductive endocrine developmental program. Finally, comparison of in vivo active genes with those predicted in silico showed relatively good agreement for brain (49%), liver (27%) and gonad (32%). The multi-tissue TRN models presented can lend diagnostic insights into the effects of changing environmental and/or genetic constraints on reproductive endocrine function.
转录调控网络（TRNs）的相互连接拓扑结构很容易以化学计量矩阵的形式进行数学（或计算机模拟）表示和分析。这样的矩阵可以使用极端途径（ExPa）分析的数学方法来“求解”，该方法可识别受转录因子（TF）可用性影响而独特激活的基因。在本论文中，利用脑、肝和性腺的计算机模拟多组织TRN模型，研究斑马鱼（Danio rerio）从受精后0.25小时（hpf；合子）到受精后90天（dpf；成年生命阶段）的生殖内分泌发育编程。首先，通过依次激活多组织模型中的所有基因来研究TRN模型的特性。该分析表明，相对于肝脏（23%）和性腺（32%），脑中共调控基因的比例最低（19%）。鉴于脑分别比肝脏和性腺多75%和25%的转录因子，这一结果令人惊讶。这种共调控能力的“层次结构”（脑<肝脏<性腺）表明脑中存在高度基因特异性的TRN，暗示其作为内分泌功能“主控制器”的作用。其次，在斑马鱼发育过程中，用不同的TF可用性对TRN模型进行约束。发育过程中活跃基因的标准化数量显示，从10至12 hpf（胚胎生命阶段）直至30至90 dpf（成年生命阶段），脑和性腺之间存在伴随激活。这表明脑和性腺之间存在一种假定的“同步”，以及早期生殖内分泌发育程序的启动。最后，将体内活跃基因与计算机模拟预测的基因进行比较，结果显示脑（49%）、肝脏（27%）和性腺（32%）的一致性相对较好。所呈现的多组织TRN模型可以为环境和/或遗传约束变化对生殖内分泌功能的影响提供诊断性见解。
